Using AI to handle Structural Changes in Time Series

In an ever-evolving world, structural changes are bound to occur. Their frequency and impact can vary between industries and use cases, but when they happen it is important to timely react to them in order to avoid unreliable models and large forecasting errors.

Let’s inspect how TIM overcomes the challenges posed by structural changes by generating and applying high-quality models in just seconds to minutes.

 

 

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Time for Time Series dives into specific features and looks at general functionalities in TIM, as well as covering many topics related to time-series analysis. We welcome everyone, from managers to data scientists, to get to know TIM and to ask your questions to our experts during the live Q&A.